{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "# 为什么一定要掌握自学能力？"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "一句话解释清楚：\n",
    "\n",
    "> 没有自学能力的人没有**未来**。\n",
    "\n",
    "有两个因素需要深入考虑：\n",
    "\n",
    "> * 未来的日子还很长\n",
    "> * 这世界进步得太快\n",
    "\n",
    "我有个观察：\n",
    "\n",
    "> 很多人都会不由自主地去复刻父母的人生时刻表。\n",
    "\n",
    "比如，你也可能观察到了，父母晚婚的人自己晚婚的概率更高，父母晚育的人自己晚育的概率也更高……\n",
    "\n",
    "再比如，绝大多数人的内心深处，会不由自主地因为自己的父母在五十五岁的时候退休了，所以就默认自己也会在五十五岁前后退休…… 于是，到了四十岁前后的时候就开始认真考虑退休，在不知不觉中就彻底丧失了斗志，早早就活得跟已经老了很多岁似的。\n",
    "\n",
    "但是，这很危险，因为很多人完全没有意识到自己所面临的人生，与父母所面临的人生可能完全不一样 —— 各个方面都不一样。单举一个方面的例子，也是比较容易令人震惊的方面：\n",
    "\n",
    "> 全球范围内都一样，在过去的五十年里，人们的平均寿命预期增长得非常惊人……\n",
    "\n",
    "拿中国地区做例子，根据世界银行的数据统计，中国人在出生时的寿命预期，从 1960 年的 _43.73_ 岁，增长到了 2016 年的 _76.25_ 岁，56 年间的增幅竟然有 **74.39%** 之多！"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "button": false,
    "collapsed": false,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "data = np.genfromtxt('life-expectancy-china-1960-2016.txt',\n",
    "                     delimiter=',',\n",
    "                     names=['x', 'y'])\n",
    "da1960  = data[0][1]\n",
    "da2016  = data[-1][1]\n",
    "increase = (da2016 - da1960) / da1960\n",
    "note = 'from {:.2f} in 1960 to {:.2f} in 2016, increased  {:.2%}'\\\n",
    "    .format(da1960, da2016, increase)\n",
    "\n",
    "plt.figure(figsize=(10, 5))\n",
    "plt.plot(data['x'], data['y'])\n",
    "plt.ylabel('Life Expectancy from Birth')\n",
    "plt.tick_params(axis='x', rotation=70)\n",
    "plt.title('CHINA\\n' + note)\n",
    "\n",
    "# plt.savefig('life-expectancy-china-1960-2016.png', transparent=True)\n",
    "plt.show()\n",
    "\n",
    "# data from:\n",
    "# https://databank.worldbank.org/data/reports.aspx?source=2&series=SP.DYN.LE00.IN"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "如此发展下去，虽然人类不大可能永生不死，但平均寿命依然在持续延长是个不争的事实。与上一代不同，现在的千禧一代，需要面对的是百岁人生 —— 毫无疑问，不容置疑。\n",
    "\n",
    "这么长的人生，比默认的想象中可能要多出近一倍的人生，再叠加上另外一个因素 —— 这是个变化越来越快的世界 —— 会是什么样子？\n",
    "\n",
    "我是 1972 年出生的。从交通工具来看，我经历过出门只能靠步行，大街上都是牛车马车，机动车顶多见过拖拉机，到有自行车，到见过摩托车，到坐小汽车，到自己开车，到开有自动辅助驾驶功能的电动车…… 从阅读来看，我经历过只有新华书店，到有网络上的文字，到可以在当当上在线买到纸质书，到有了国际信用卡后可以在 Amazon 上第一时间阅读新书的电子版、听它的有声版，到现在可以很方便地获取最新知识的互动版，并直接参与讨论…… 从技能上来看，我经历过认为不识字是文盲，到不懂英语是文盲，到不懂计算机是文盲，到现在，不懂数据分析的基本与文盲无异……\n",
    "\n",
    "我也见识过很多当年很有用很赚钱很令人羡慕的技能 “突然” 变成几乎毫无价值的东西，最明显的例子是驾驶。也就是二十多年前，的哥还是很多人羡慕的职业呢！我本科的时候学的是会计专业，那时候我们还要专门练习打算盘呢！三十年之后的今天，就算有人打算盘打得再快，有什么具体用处嘛？我上中学的时候，有个人靠出版字帖赚了大钱 —— 那时候据说只要写字漂亮就能找到好工作；可今天，写字漂亮与否还是决定工作好坏的决定性因素吗？打印机很便宜啊！\n",
    "\n",
    "这两个因素叠加在一起的结果就是，这世界对很多人来说，其实是越来越残忍的。\n",
    "\n",
    "我见过太多的同龄人，早早就停止了进步，早早就被时代甩在身后，早早就因此茫然不知所措 —— 早早晚晚，你也会遇到越来越多这样的人。他们的共同特征只有一个：\n",
    "\n",
    "> 没有自学能力\n",
    "\n",
    "有一个统计指数，叫做人类发展指数（Human Development Index），它的曲线画出来，怎么看都有即将成为指数级上升的趋势。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "button": false,
    "collapsed": false,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "plt.figure(figsize=(10, 5))\n",
    "\n",
    "lebdata = np.genfromtxt('life-expectancy-china-1960-2016.txt',\n",
    "                        delimiter=',',\n",
    "                        names=['x', 'y'])\n",
    "\n",
    "hdidata = np.genfromtxt('hdi-china-1870-2015.txt',\n",
    "                        delimiter=',',\n",
    "                        names=['x', 'y'])\n",
    "\n",
    "\n",
    "plt.plot(hdidata['x'], hdidata['y'], label='Human Development Index')\n",
    "plt.tick_params(axis='x', rotation=70)\n",
    "plt.title('China: 1870 - 2015')\n",
    "\n",
    "plt.plot(lebdata['x'], lebdata['y'] * 0.005, label='Life Expectancy from Birth')\n",
    "plt.plot(secondary_y=True)\n",
    "\n",
    "plt.legend()\n",
    "\n",
    "# plt.savefig('human-development-index-china-1870-2015.png', transparent=True)\n",
    "plt.show()\n",
    "\n",
    "# link:\n",
    "# https://ourworldindata.org/human-development-index\n",
    "\n",
    "# data from:\n",
    "# blob:https://ourworldindata.org/44b6da71-f79e-42ab-ab37-871e4bd256e9"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "社会发展越来越快，你要面对的人生越来越长，在那一段与你的直觉猜想并不相同的漫漫人生路上，你居然没有磨练过自学能力，竟然只能眼睁睁地看着自己被甩下且无能为力，难道接下来要在那么长的时间里 “苦中作乐” 吗？\n",
    "\n",
    "没有未来的日子，怎么过呢？\n",
    "\n",
    "我本科学的是会计，研究生跑到国外读宏观经济学没读完，跑回国内做计算机硬件批发，再后来去新东方应聘讲授托福课程，离开新东方之后创业，再后来做投资，这期间不断地写书…… 可事实上，我的经历在这个时代并不特殊。有多少人在后来的职业生涯中所做的事情与当年大学里所学的专业相符呢？\n",
    "\n",
    "纽约联邦储蓄银行在 2012 年做过一个调查，发现人们的职业与自己大学所学专业相符的比例连 _30%_ 都不到。而且，我猜，这个比例会持续下降的 —— 因为这世界变化快，因为大多数教育机构与世界发展脱钩的程度只能越来越严重……"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "button": false,
    "collapsed": false,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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sp96bALRWzrw4a1ohDXs/xajK81FY1ru7/aFPV+H4nk9Q9fX/xECnN/b33Lg2xyEAQPnYShzasgZXfut+tJ88BndLw/C/CSJtWVBdU5eRE3bOheZDBMACAOWjKqcXF5WPMoouJl2ObFuHaRf1/ntu2LsZuz54GVff+z/IyRv4OIRTn5to23srsPCGbyIaiUCORgAAkiQhHAoMX/FE2lUtugC10XSIxE4tvBWAyzB78XzR9aRLOBhA4/7PcN68y3uuWV97BKFuH1b9+d/x9wersfGVPwAAutxtWP3ETwZ8blz9rg0YPXkmistHI7+oBGOnzMYbv/0WJEgYNWl66t8YkfrdWl1TVy66CDXR9DoRo8l8IYAfSzq9verr//lvOXkFpaJrIqKMd1/t8qq/iC5CLTTdEgFwJQBf5YWXTGWAEFGafEN0AWqi2RAxmsxlUMZD2iZMn5c1XVlEJNzi6pq680UXoRaaDREA8wFI+cVluaWjJ84UXQwRZZVviC5ALTQZIkaTWQJwFQD3eXMvn63jsmoiSq+vVdfUafL353DT6g9hEgADAPcY4yx2ZRFRulVC+UM262k1RC4GEKmYMGVkYdlIg+hiiCgrfUN0AWqguRAxmsw5AK4A0GaYs3ie6HqIKGvdWl1TVya6CNE0FyIALgBQAiBQMf48Hn9LRKIUAlgqugjRtBgilwMIVEyYMjKvsGSU6GKIKKvdKLoA0TQVIkaTuQTAIgBtE2bM5zxtIhLtumyfpaW1Nz8TSs2REePPmyG6GCLKeqMBDHx4T4bTWogsAhDIKyzJKyrLnh17iUjVsrpLSzMhEjs3ZD4A16SZi6ZKOp1edE1ERABuEF2ASJoJEQDnAcgFEB5VOYPjIUSkFvOqa+oqRRchipZCZDYAGZBQOmoCx0OISE2ytktLEyES2ytrMYD2sVMunJCTV1AiuiYiogQMEZUbDWAMgK5xU+awFUJEanNldU1doegiRNBKiPSMgZSPNfCcViJSm0IAZtFFiKCVELkEQJc+N19fUDJiouhiiIj6sVh0ASKoPkSMJnMBgAsBtI8xzhzPqb1EpFKXii5ABNWHCICpACQA0YoJU7N2Gh0RqV5WrlzXQoicF/+kdNR4hggRqdXo6pq6rJv4o4UQmQ3ACwBFZaMYIkSkZlnXpaXqEDGazHoA0wF4ispHF+UWFI0QXRMR0QAYIiozFkAOgMiY82axFUJEascQUZme4CgfO5khQkRqN7e6pq5IdBHppPYQOR9AGABKKsYyRIhI7XKgHFmRNdQeIhcC8EiSTuIiQyLSiKya6qvaEDGazEUAJgDwjRhvrNDn5OaLromIaBBMogtIJ9WGCIBJAGQActnYytGiiyEiGqRZogtIJzWHiAHKSnWUjBjHECEirbhAdAHppOYQmQHADwCFZRUMESLSitJsOulQzSEyGYAPAPKLyxkiRKQlM0UXkC45ogvoT2yl+jgAjQCQX1gySmxFRESnk+WoHOr2dwQ6O7py8gs2FJWN2gjgEICtomtLF1WGCIAKxHbuzS8qzdfn5mXV4h0iUg9ZluVwMOAJ+r3OQJfHFehsd3Z1tDg9bY0ud7OjPRoJRaGM4b5pt1nfEV1vuqk1REZDmZmFsjGV3C+LiFIuHAx0Bv1eV3dXp9Pf2e7scre6Op0nne7m4+3hYCA8wFP1AKIApqSpVFVRc4joAaBk5LgKwbUQUYYIh7p9IX+Xs9vX6fJ3tjt97jZnp6vJ1dFkd4YCXaEBnqqDcgRu/Nbn20LperelqGxVU2uITAAQAoDC0pEMESIatEg4FAj6u1zdPo8z4O1w+jxOl9fZ5Oxotju7uzzdAzxVQt+g0EFpYUixj80AjgBwxD53AnAB8NhtVjmFb0nV1BoiEwEEAKCgpJzdWUTURzQSDgb9Xa5uf6cz4HW7/B6n0+tqcrqbHS6fx+kb4KkSgHwARVCCIt4VJcXubwFwEIAdQBOUkHACcNtt1miq3o+WqTVExiMWIrkFxaWCayEiAaLRSDgU8Lm6fZ2u7i630+d2Or3tLS5Pq8PpdTV7z/L0xKDIBRCBEhQSlFA4CuA4gJOxr50AOuw2ayRV7ydTqS5EjCazDsAYxKb36nPzTu1/JKIMIUej0VC3r73b53V2d7mdPo/L1dXR4vS0nnB5Wk+4Y/NrziQPSkgUxT5PDIoOKN1ODgAN6O16ctlt1oEGyWmIVBciAMrQ2weJnByGCJGWKWspAh3KzCe30+9pd3Z1tLg8rSec7taGDjkaGSgpctE7RpGP2H56ULqhPFD+2EwMCieUoAim8j0NhcPhyAFwHpRdOGZAOeJiBoCdBoPhxwJLGxZqDJGSxC90ObkMESKVk2UZ8bUU3V0ep7+z3dXlbnV2tjY63S2Ojkg4OFA3UQ56g6IAvUGhg7L10YnY7TiANsTGKew2ayCV72koHA6HDspakcSQiN+mQAnDUxWnrcAUUmOIFCKhDatnS4RINcLBgDfo73J2+zwuf2eH0+dudXa2nXR1NB93hYP+s62lSAwKoDcouqEMYu9Bb1DEWxV+Nc18cjgcE3F6SJwPYCp639dgTRve6sRQa4hIAKDPzdfr9Pr+EpyIUiQSCvqCfq+r29fp9HvbnT53zxRZV9DvHaib6NS1FPFuaQnKeEUTlJlPx6HMgoqPU3hVFhRjcXpIzAAwHcPbehjvcDiKDAbDQLPJVE/VIVJYOoKtEKIUiIRD3aFAl7O7q9MZ6Opw+dxOp9fV5OpotjsDXvdA3UQSlL+44zOfTl1L0QLgGJSgiK+lcEJlaykcDkcFTg+J+K08jaUYAexL4+sNO1WHSH5xOUOEKEnRSDgUDPhcQZ/HGfAqM5+87c1Od/Nxp8/dNpi1FPGZT6eupWiD0qJwoHeKrAvKFFnVrKVwOBwl6D8kzgeglk1dx4EhMuzKoTR9kV9UyhAhGkBsLUV70NfpDHS5XX6Py+ltb3a6WxpcXldT51menhgUOegNivhainooLYpG9C66a1fTWgqHw1GAvgGRGBrjBZY2WONEF3Cu1BoiIQDIKyxhiFDW61lL4fe6urs8Tr/H5fK2tzg9bQ3OztZGjyxHB+omiq+liE+RjaJ3QNsNZWqsA8rsp8S1FAPtI5VWDocjF8ogdH9BUYneFpIWaSHoBqTGECmDsqEZcvOLGCKUFWRZlsPdfne3MkXW5e90Obs6Wp2dbY0ud4ujIxoJD9RNdKa1FDoAXigBEQ+LeIvCZbdZB9pHKq0cDoce/a+lmAFl3EAvrLjUYkskBUoRa4no9PpM/YdDWah3LUWXq9vndvo7O5y+jlZXp7PR2dF0vP0sayn06B3MPnUtRQC9i+4c6J0i67LbrP5UvqehcDgcEpS1FP2NUZxpLUWmY0skBUoRa4kQaVE42N0V9HudsV1kXV0dbc74uRShbt9gthsvwulrKYJQBrH3QhmnaEVvq8KnsplPE9B/UEzD0NdSZDq2RFKgBMDZBgSJhIqEg/74ortAZ0efcykGsZYicYrsqWspmgEchrKLbCt6xyk6VRYUY3DmtRQlAzyV+mKIpEAu4ivWZVk1/9NQ9omtpXB1+5Ttxn3uNmdsiqzL39k+UDdRfC1FvFWRuJZChrKWYi+UrqfE7cY9KpsiOwJnXkvBIxqGx2jRBZwrNYYIUdpEI5FQLChcgS630+dxOrtczS53S4Ozq6Ola4CnJq6lKETfKbKAMi5xGErXUxN6F925VTZFthhnXkuh+V9wGqD5/bMYIpS1fB7n8Y0v/+GvZ9luPDEoTt1uvB3KWgoHlIHteNdTu5q2G4+tpZiO/rufJggsjU4/aldz1Bgi7MKi9JBlOfbPLRe9YxR56LvdeAeUKbLx7cYTp8iqbS3FVPTf/WSAttdSZDKGSArIp31ClALRSCQfwGQAXVBaEsfR9wAjpwrXUhjRf/fTecjctRSZTOdwOPINBoNq/p0NlRpDhCgtCstG1gP4FxWupajEmddS5ImrjlKkCMp2+JrEEKGspc/J7RYVILG1FP2NUUxDBnRx0JAUQRlf0yR1hwin+JKGORyO0eh/jGI6lEW1RIDG/2hQdYiEuv2qOf6SqD8Oh6Mc/Y9RzABQIbA00g5Nr+JXdYgEA12q6aum7JWwlqK/7qcxAkujzKCadUPJUGOIyIhNRwz6PAwREsrhcBRC2QmXKFVUs6YoGTrRBfTDj9hUxUAXQ4SE4/oKSjXVrDdKhhpbIp1QDqYK+D3tmj7AnrTp6quvHglgPoDJJSUlU//0pz+JLokym6ZbImoMEQ9i5x+Hg/5wNBoJ63R6NdZJmasKwFcAtEWj0YF25CUaDpoOETV2Z3mQcDhNNBxilxaJ0A6gWZIkjodQqmm6O0uNIdKBhBCJhIIMESLKZGyJDDM3EvYACoeDHBchokzGlsgw6xMabIkQUQYLGQwGTf+hrMYQ8UM53AcAEO72D3QwEBGRlml2z6w4NYZIn1QOeDs0/0MmIjoDl+gCzpUaQ6RP91WXu80pqhAiohRjiKSADwmrhDvbGjX/QyYiOgPN/35TY4h0xD5KANDRfNwlc0t4IspMDJHhZrdZIwDaENseORLqjoSDAY/YqoiIUoIhkiInkHBQS9Dv5bgIEWUihkiKOKAcGQkACHR5NP+DJiLqR4PoAs6VWkPkJBJqC3S2syVCRJmoXnQB50qtIeJCwoLDLncrWyJElInqRRdwrtQaIk70meZ7kiFCRJkmAnZnpUzfab5Ndlc0GtH0TpdERKdoNBgMmt58EVBpiMSm+bYgNkMrGglFu73uk2KrIiIaVvWiCxgOqgyRmD7TfLs6WjXf7CMiSlAvuoDhoOYQOYaEab7uFgdDhIgySb3oAoaDmkOkPvGLNsfBE4LqICJKhX2iCxgOag6RBiTM0PK0NrjDwUCnwHqIiIbTLtEFDAc1h4gHyiytgvgFn8fF1ggRZYIggAOiixgOqg0Ru80qQ2nulcWveV3NHBchokywz2AwZMSyBdWGSMw+JLREOpqOMUSIKBNkRFcWoP4QaQDQc5ZIy7G9jbIc5dkiRKR1DJE0aYx91AFAqNsX6u7qbBZYDxHRcLCJLmC4qDpE7DZrEIAdQEn8Wqez8Yi4ioiIhgVbImm0B0Bp/IuW+n2HBNZCRHSuHAaDIWO2cdJCiBxBQp0nD20/HgmHAgLrISI6FxtEFzCctBAix6AsOpQAQI5GZK+r6bDYkoiIksYQSSe7zeqGMi7S06XlOnGEXVpEpFUMEQE2ARgR/6LxwGeHZVnmVF8i0poOALtFFzGctBIifTYq83mcvkBnO7dAISKtsRoMhujZH6YdWgmRBgBdAPLjFzqajx8UVw4RUVIyqisL0EiI2G3WKIDNAEbGrzUftTFEiEhrGCIC7QCQG/+i1b6vOdTt9wish4hoKDqhjO9mFC2FyGEo+2j11OxpbdgvrhwioiFZZzAYQqKLGG6aCRG7zeoHsB8Js7Qa9m3ZIa4iIqIhWSW6gFTQTIjEfIqEfbRaju0+2e3rbBFYDxHRYL0vuoBU0FqI7EPC6nUAcDoO7hRXDhHRoOw2GAx20UWkgqZCxG6ztgI4CKAifq1+18e75Gg0o+ZdE1HGeUd0AamiqRCJWYuELVC62lu83o4Wbg9PRGr2tugCUkWLIbIbQBhATvxCy9HdHGAnIrVqhrLOLSNpLkTsNqsPgBXAmN5rGw9we3giUqmVmbbVSSLNhUiMFUBe/ItIqDvS0Xw8ozY1I6KM8aLoAlJJqyFyGMpumIXxC437uWaEiFTnmMFg+ER0EamkyRCx26wRKAPso+PXmo7sOtHd5eGaESJSk5dEF5BqmgyRmC04pf6mI7sybl8aItK0F0QXkGqaDRG7zdoMpVurZ83I0W3rbOFQd5e4qoiIeuwyGAx7RReRapoNkZgPAJTFvwgHA2Gn4+BWgfUQEcVl9IB6nNZDZCcAPxIOqzq89YMt0WgkIq4kIiJEwBBRP7vNGoCyqdm4+DVfR2uXu/n4LnFVERHhHwaDwSG6iHTQdIjEbIByzog+fuHIZ2s3yrIsiyuJSP0aGxvx5S9/GVdeeSWWLFmCp59+GgDwz//8z1i6dCmWLl0Ks9mMpUuXnvbcQCCAm266Cddeey2WLFmChx56qOe+73//+7jmmmvw4IMpjZeXAAAbUUlEQVQP9lx75JFHsGbNmtS/KfX4s+gC0iXn7A9RN7vN2m40mTcAWAygEQDaG486O9sa95WNmXSh2OqI1Euv1+PnP/85TCYTvF4vbrjhBlx++eX48597f//96le/Qmlp6WnPzc/Px8svv4zi4mKEQiEsW7YMV1xxBQoLlaVba9aswbJly+DxeOD3+7Fjxw7867/+a9rem2CHAWRNYmZCSwRQBthzkbBF/LEddRl3ljHRcBo3bhxMJhMAoKSkBNOnT0dTU1PP/bIs491338Utt9xy2nMlSUJxcTEAIBwOIxwOQ5Ik5OTkIBAIIBqNIhQKQa/X46GHHsIPf/jD9LwpdXjSYDBkTU9IRoSI3WZ1ALAhYT+tlmN7Tnrbubsv0WA4HA7s2bMHCxYs6Lm2efNmjB49GlOmTOn3OZFIBEuXLsWCBQtw2WWXYcGCBZgxYwYmTpyI66+/HjfeeCPq6+sBAHPmzEnH21CDAIAVootIJ813ZyV4B8B/Jl6w7/zoo9lVX5omqB4iTejq6sJ9992HX/7yl326rt56661+WyFxer0eq1atgtvtxre//W0cOHAAF1xwAe6///6ex3zzm9/Eb3/7W9TU1GDv3r24/PLLcdddd6Xy7Yj2isFgcIkuIp0yoiUScxjAIQCj4hcaD2473uk8eUBcSUTqFgqFcN999+G2227Ddddd13M9HA5j1apVuOmmm876PcrLy3HppZeirq6uz/U1a9Zg7ty58Pv9OHDgAB5//HG88cYb8Pv9w/021CRrBtTjMiZE7DarDOAtJBxYBQAHN73/gSxHs6Z/kmiwZFnGj370I0yfPh333ntvn/s2bNiAadOmYcKECf0+1+l0wu12A1BmasUfHxcKhbBixQp85zvfgd/vhyQpw5XRaBTBYDBF70i4DQaDIWPPDTmTjAmRmL0AHEjYCsV14nBb+8n6beJKIlKnLVu24I033oDVau2Z0rtu3ToAwNtvv42bb765z+Obmppwzz33AABaWlpw55134pprrsGNN96Iyy+/HFdddVXPY5999lksW7YMhYWFmDVrFmRZxtVXX41FixahvLw8fW8yvX4jugARpExbTmE0mWcD+BGA+vi14oqxJZfe/r3v6/Q5ucIKIzVaX7u8qurUi1dfffXtAJYCaCwuLs6tqan5WdorI63ZbjAYFoouQoRMa4kASmtkDxJWsXe1t3hb7fus4koiogyXla0QIANDJDY28iqAAiS8v/0b37GGg9zhl4iGlyzL+wG8IboOUTIuRADAbrPaAWwEMD5+Lej3BhsPbqsTVhQRZSRJkh7M5DPUzyYjQyTmLSj7afWshTn06fvbuv3eNnElEVEmkWXZDuB50XWIlLEhYrdZW6Hs8NszRzEaCUeP2zZ+IK4qIsokkiT91mAwhEXXIVLGhkjMKgAhKOMjAID6HesPdLqaDokriYgygSzLBwA8LboO0TI6ROw2qxfASiTM1AKAvXWvvxuNhDN2xRMRpZ4kST/N9lYIkOEhErMBQDsSVrJ72k54Tuzfym4tIkqKLMufGAyGv4uuQw0yPkTsNms3gL9B2eG3Z6v4/Rvf2eLzuLLi5DEiGl6SJP276BrUIuNDJGYngE0AJvZekrHv4zff5nnsRDQUsiz/3WAwcPFyTFaESGwB4ksAwgAK49ddJw63tRzd/ZGwwohIU2RZDkuS9FPRdahJVoQIoByjC2U+9/jE63vWv7Ghu8vTIqYqItKYJw0GA4+XSJA1IRLzCYDdSAiSaCQUPfDJP96SM20nSiIaVtFotFWSpP88+yOzS1aFiN1mjUIZZM8BkBe/3nzU1uh0HPxUWGFEpHo6ne4HBoPBLboOtcmqEAEAu83aDGWDxomJ123rXl3Lbi0i6k8oFPrIYDC8KLoONcq6EIlZB+W8kdHxC+GgP7z7w5WvchEiESWKRqOh3Nzce8/+yOyUlSFit1nDAFYAKEbCBo2uxiNO+64N7worjIhUJxqNPmgwGA6KrkOtsjJEAMBusx4H8DoAQ+L1w1vW2NpPHtsupioiUpNQKGTPycn5teg61CxrQyTmfSiztSYkXtyx+vn3OD5ClN1kWZZzc3P/yWAwdIuuRc2yOkTsNmsEQC2AIBL21uL4CBF1d3c/aTAY1oquQ+2yOkSAnkWIf4YyyH7q+Mg/hBVGRMIEAgF7QUHBv4muQwuyPkQAwG6z7gPwGk4fH9nF8RGi7BKNRiMA7jAYDAHRtWgBQ6TXezjD+Eigy9MspiQiSrfOzs6HZsyYsUV0HVrBEIkZaHxk5+rnXgwHA53CiiOitOjq6tpbXl7+M9F1aAlDJMGZxkc8bSc8e+pef5ED7USZKxwOB3Nycm4zGAw8HmIIGCKniI2PxNeP9Bxi1VK/p+nQ5jWvyXKUGzUSZSCv1/uD6dOnc1HhEDFE+vcPAJtxykD7cduGQw17P31PTElElCpOp/N1k8n0uOg6tIgh0o/Y+MjTAI7hlIH2/Rvf2dpq389TzYgyhNvtrpdl+aui69AqhsgZ2G3WAIAaAJ1I2KgRAHasfs7iaT2xV0hhRDRsuru7/Y2NjdcvWLCAq9KTxBAZgN1m7QDwBwB6JMzYAmR89o+n/+73uBoElUZE5ygajcp2u/2+a665Zp/oWrSMIXIWdpu1EcDDAEYCKIhfDwcD4W3v/fWlYKDLJaw4IkpaQ0PDiiVLljwnug6tY4gMgt1mPQDgSSgHWfVM/fV5nL7t7z/7t1DA1yGsOCIaspaWlp3bt2/nGSHDgCEySHabdROUExEnI+Hn5mltcG97/5lnGCRE2tDR0dFSX1+/5Hvf+x6n6w8DhsjQvAfgQyhB0rOGhEFCpA0+n8+3c+fOpcuWLXOKriVTMESGwG6zRgE8D2ArGCREmhIOhyNbtmypvvvuu7mp6jBiiAyR3WYNAfgLgM/AICHShGg0Klut1l/dfffdL4muJdMwRJJgt1mDYJAQacaWLVuee+aZZx4QXUcmYogkiUFCpA27du368Mknn6y2WCwcSE8Bhsg5GEyQBP1eDuARCbJnz57PHn744ZstFktIdC2ZiiFyjs4WJJvffPxpn9t5XFR9RNlq7969ex599NGlFovFK7qWTMYQGQYDBYm/s92/6Y1H/+ZucewWVR9Rttm/f//hxx577IZ333237Vy/lyRJsiRJzyV8nSNJUqskSe+e5XmLJEn60zm87nmx1/5VwrXRkiSFJEl69CzPrZIkyTyI73/Ov5cYIsPklCA5Dwk/20ioO7L5zSdebzm252NB5RFljcOHD9c/8cQTt7z99tv2YfqWXQDmSJJUGPv6agAnzvYkWZa3yrL8/cG+iCRJOf1cPgrgxoSv7wCwZxDfrgrAgCEyXBgiwygWJE8AWAslSHJ775Wx0/LCOvuuDW/L0WhUSIFEGe7YsWMNTz755K2vv/76cO+y/T6AG2KffwVAz1RhSZIuliTJKknS9tjHC2LXq+KtFUmSRkqS9KYkSbskSdokSdLc2PX7JUn6iyRJawD8rZ/X9QPYJ0nSotjXX4ayc0b8tW+SJOnT2Gt/IEnSOEmSzgPwHQD/JknSDkmSLo9d/7skSTtjt3jA6CVJekqSpD2SJK1JCMpBY4gMM7vNGgbwHJR/ZJUA+vxHObjpve0HPnn3hUg4xK2niYaR3W5vfOqpp257+eWXd6bg278M4E5JkgoAzAXwacJ9+wF8QZblBQD+C8Bv+nn+fwPYLsvyXAA/Q9/AuAjALbIs33WW164EEAHQmHDfBgCXxl77ZQA/lmW5Hsofs3+UZXm+LMsfA/gTgPWyLM8DsBC9rZkZAB6TZXk2gA4Ay87+o+irv+YTnSO7zSoDeN9oMrcB+C6U/zie+P2OPZuO+js7Vsy54o6v5uYXlomqkyhTHDp0yP7444/fuXLlyq2p+P6yLO+K/YX/FSjbHyUqB/CsJEkzAMjo0wPR4zLEfkHLsrxOkqRRkiSVx+57W5Zl/wAvvwrArwA0A3jllPsqAbwiSdIEAHlQDtLrz5UAvh57/QgAtyRJFQCOybK8I/aYeFf8kLAlkkJ2m3ULgN8CyMcpB1u1Hd/fsvWdvzzl7+xo7PfJRDQoNpvt8B/+8Ievrly5clOKX+ptAL9HQldWzK8AfCjL8hwANyHhyIgEUj/X4utWugZ6UVmWg1B+wf8QwOun3F0D4FFZlk0A7jvDaw8ksUckgiQaFgyRFLPbrIeg/CPzQdlKvofX1ez9ZOXDK9ocBz/t98lENKDNmzfve+SRR6rffffdjWl4uRUAHpBl2XbK9XL0DrR/4wzP/QjAVwFlrARAmyzLnjM8tj8PAfgPWZZPXXeW+Nr3JFzvRJ+D9LAWSq8IJEnSS5I0bD0gDJE0sNusTQB+DaAep0wBjoSDke3vP7Pq8JY1r0TCoYCgEok0p66ubvsTTzxx7+rVq9en4/VkWW6QZfmRfu76HYDfSpK0EcopqH2eFvt4P4BFkiTtAvD/0PcX/mBee48sy8/2c9f9AFZKkvQxgMTpzO8AuC0+sA7gXwFcIUmSDUqrZvZQXn8gkixzJ4B0MZrM+QC+CWXqnQNAn1W05eMmjzBdeecdhaUjJvb3fBp262uXV1WdevHqq6++HcBSAI3FxcW5NTU1P0t7ZXRGsizj/fff/+S11177nsVi2Sa6njORJGkZgJtlWR5SYGgNWyJpZLdZu6GsJXkBwCQAIxLvdzcf72D3FtGZhcPh8Kuvvrr2tddeq1Z5gNwM4H+gnIia0RgiaWa3WaN2m3U1lO4tGUqY9Ih3bx3avJrdW0QJfD5f12OPPfbm6tWr77NYLMO9DmRYybL8tizLM2VZtoquJdUYIoLYbdbDAH4JYDeAKThlWmD9jvX7P3u39kl/Z/tZV8YSZbrW1tbW3/zmN6/s3Lnz3ywWyxHR9VAvhohAdpvVA2WK3gtQZm717d5qcXRYX314RfNR23qucqdsdejQoWMPPPDAc42NjT+zWCwNouuhvrjYULDYkbtrjCbzUQD/AqV7qxGxWR3RSCi664OX6sYYZ+2b+fmbby0oKR8vsFyitNqwYcOuv/71r8/JsvykxWLpFF0PnY4tEZVI6N6yQVk1mpd4f6t9X/PGVx56qunwzg/laDQioESitAmFQsGXX375oxUrVvxeluVHGCDqxRBRkVj31qMAngcwDsDYxPujkXDUtu6Vj7avevZJn4dnlFBmcrlcrQ8++OB7a9aseQDA8zxQSt3YnaUyse4ti9Fk3gNlTcn5ULq3erYncDYcat348h/+esHi6xdOmnXx1fqc3KFudUCkSjabbc/jjz++KRAIPGyxWHgGjwawJaJSdpu1EcrK1r9B2XdrXN9HyDjwyT+2bXrj0UfdzY5Tt2Eg0pRQKBRcuXLlh3/84x/fCwQCv2SAaAdbIipmt1kjANbGWiVfh7JVQTOUfbgAAL6O1q7Nbz3+xsQLLto6deGV1xSWVkw6w7cjUiWXy9X82GOPfXLs2DELgL/xOFttYYhogN1mbTKazL8HcDGUMBkJpYurZ9pv44HPjjce+Kx26sIrLzTMWbwkr6B4pKByiQZFlmV5+/btO5966qld3d3dzwBYb7FYOJVdYxgiGhEbK9lkNJn3AfgSgC9AOaekPfFxR7et21u/8+P95y++ftGEGfO/mJObXySgXKIBdXZ2up577rlPtm7duh/AoxaLpV50TZQchojG2G1WN4CnjSbzRgB3Q5kO3IqEMwmikVB0/4a3Nh/9bO2OmZfd/Pkxk2ct1un1/R2UQ5RWsizDZrNtfeKJJw4GAoENAJ5j95W2MUQ0ym6z7jeazL8E8DkAdwIwAmhCwiyuoN8b3GV58cOSkeO2XGC+6YqKCectkCRdf4fjEKWc1+ttf/7559dv3rzZCWWXhjqLxcJtxDWOIaJhsYH3TUaTeTuALwK4HcoeXCcBhOOP87qavZ+9W/vOyEnTP5m68MrPjxg32STpdKeee0CUErIsy7t37/7siSeeOOD3+/cBWGGxWE6KrouGB0MkA8S2mF9jNJk3AbgWylkYESgtk56BSteJw22uE4ffKhk5ft20RVddMqpyxkVcY0Kp1NbW1vD8889/smvXrk4o54Ovs1gs4bM9j7SDIZJBYiveVxpN5vUAboVy+JUfQAt6T1iD19XUuXPN8x/kFZZ8NP1z1ywcO2X2pbn5heViqqZMFAgEutatW/fha6+95gRwBMDTFoulUXRdNPwYIhnIbrO2APiL0WReA2Um1xwoYyXNSGiZBP3e4N6P3ti0f+Pbm6cuvHL2hPMXmAuKucEjJS8ajcp79+7d/PTTT+9xu90A8CqAtWx9ZC6GSAaz26z1RpP5IQAGKN1ci6G0SJqQcDRvNBKOHt6yxnZ4yxpb5YWXTjXMvmRx8Yix0yRJ4iA8DVpzc7P9hRdeWL97924JwD4AL7L1kfkYIhnObrPKAI4DeMpoMv8dQBWAq6EMwLdC6e7q0bB309GGvZuOlo6eWGY0XTZ3VOX0+XmFJaPSXTdpR0dHR/Pq1avXr169uguAG8pWPTs48yo7MESyiN1mbQPwmtFkXgWlVXIzlD25XAA8iY/tbGv07P7w1Q0ANoyfPr9y0syL5pePnTybA/EU19nZ6aqrq6t78803W2VZzgXwNoA1FovFf7bnUuZgiGQhu83qhbJT8HoAC6EMwhuhjJu0QpnZ1aPp8I6GpsM7GnLyClZNNn3+gnFT5swvrhgzjWtOspPP5/Ns3Lhx/cqVK4+Gw+GRULquXrZYLM2ia6P0Y4hkMbvNGoSyzmQzgJkALoeyeFEPpVuiI/Hx4WAgfPSztXuOfrZ2T8nIcSVG02VzR0yYMrOwdEQlAyXzBQKBri1btmx86aWX9gUCgRFQNgJ9GsBudl1lL4YIxffl2gtgr9FkfgHAXABXAZgCZSD+tLETr6vZu2f961YA1sLSisKJMxdNHzVx+oySUeOm63PyCtP8FiiFvF5v+6effmp9/fXXDwQCgZFQFrI+BmCbxWLhKZtZjiFCfcS6uqwArEaTeTyUlskSKKcsBqEESp/pmv7Odv+RLRbbEVhskk4vjZ8+r3LseReeXz6mckZ+cdm4U1+DtMHlcp3csGGD9Z133jkSiUTGQvl9sQLAJp42SHEMEToju83aBOAdo8n8HoDpAC4DcCmU7q4wACcS9uoCADkakU8e3OY4eXCbA8DastGTyiacv2DGiHHGqYVlIytz8wvL0vw2aAhkWZYdDsfBtWvXfvLxxx83Q/njoRTKXlcbLBZLQGyFpDYMETqr2B5dBwAcMJrMLwKYBmA+lPNN4i0NN5QZXn36xj1tJzyethOfAfgMAEpGji8dY5xVWT62srJ4xNjKgpIRE7jDsHh+v9+7f//+HatXr9528ODBEIBRAEoAvATAarFYugb+DpStGCI0JHab1Q9gN4DdsUCZBGAWgEugjKEAQADKtOHTVil7XU2dXlfTPigzeqDT5+hGGy4YO3LS1MrSURMrC8tHTcrLLxop6XQ8ujnFZFmWGxsbj2zatOmz1atXHwyHwyMAlEH5b7cCwGaLxdI98HehbMcQoaTFBuQdsdsao8lcDmAGgIsALICyoFGCEiqe2Mc+opFwtKV+T1NL/Z4mAFsBQKfP1ZWPrRxROnrSqOIRY0YWllaMyi8uG5lfWDIqJ7+wnCvpz43P5/Ps3r1726pVq7bX19d7oXRZTYayx9UKKLOtuE0JDQpDhIZN7MCsrQC2Gk3mHCitlHhLZRaUX1Tx7i4vlGA5bXZPNBKKtp885mo/ecx16n36nDx9+bjJFaWjJ4wsKhtdkVtQWJSTV1CYk1tQlJObV6jPzSvU5+QV6nJyC/U5ufkpequaEwgEfMeOHdu3devWPevXr6+PRqPFUI5ZLgewGYAFwDFO1aWhYohQStht1jAAe+xmBQCjyVwGoBLKaYyzoQzW50BprchQphH7oLRY+j1rOxIORmJb2redrQadPkdXUFpRWFBcXphXUJQv6fS6aCQ81jD70mcrJkxphzKOk7HiwbFly5Y9H3/8cX0kEtGht9XRDOB5AFstFotnwG9ENACGCKVNbKv6vbHbe0aTWQ/ll9okABOgbBRZGftcByVYdFACxZ9wG9Rfy9FIOOrraO3ydbQmDgrLzUdtn9ht1hPD867Uxefzeex2+8EtW7bsjQWHDKW1MRnKGJUVwMcAjlosln6DmmgoGCIkTGzW18nYrYfRZNYBGAGlu2UUlBlgRgAToYRMvOUSDxMp4RaBskNxOHaLPyb++Iw60TEcDoeamprqjxw5cmTr1q1H9uzZE2+hlUMJZQnAMQCvA9jOWVY03BgipDqxAXtX7HY48T6jySwByAdQGLsVJXxeCGV2UTmUECqCEhq6hFszNNyNFY1G5Y6Ojia73X7UZrMd+eSTT453d3fHx5XiLY54cLwFZZD8rF1/RMliiJCmxLa2D8Ru7YLLSblAINDV0tLS0NDQ0HDo0KGG7du3N3o8nmDs7hworbVCMDhIEIYIkUr4fL5Ot9vd2tra2lJfX3/CZrM1HDlyJHETTAlKS2s8lK65EAAblIWchxkcJAJDhCiNotFo1OfzuTs6OtqcTmfryZMnW48fP962f//+1o6OjlMX9umghEZZ7HMAqAewBsoOAse5noNEY4gQnaNIJBIJh8PdoVCoOxQKdXd3d/u9Xm+nx+PxdHR0eFwul6elpcVz8uTJzsbGRq8sn3FyWXxMJx+9EwHsADZAGRs6arFYvOl4T0SDxRAhGoDf7w+vWLHir7Isy9FoVI5Go3IwGAx7vd6g2+3udrvd3QkD24OVB2XQvxjKwH8USkvDBWWx5j4AJwA0crdcUjuGCNEAotGovGHDhuNDfJoeSmsifstDb8tCB6ALylYxx2If2wC0cNEfaRFDhKh/8a6l+PoTHZRw0EP5/ya+3kROuMUfG4KyTX4TlPNXmqHMJGuFEhhd3F6EMgVDhOh0hwHsh9LNFEHvTKiu2M0b+xiAcp5KN5SV9B4AnQACDAnKFtIAg3xEREQD4pkNRESUNIYIEREljSFCRERJY4gQEVHSGCJERJQ0hggRESWNIUJEREljiBARUdIYIkRElDSGCBERJY0hQkRESWOIEBFR0hgiRESUNIYIEREljSFCRERJY4gQEVHSGCJERJQ0hggRESWNIUJEREljiBARUdIYIkRElDSGCBERJY0hQkRESWOIEBFR0hgiRESUNIYIEREljSFCRERJY4gQEVHSGCJERJQ0hggRESWNIUJEREljiBARUdIYIkRElDSGCBERJY0hQkRESWOIEBFR0hgiRESUNIYIEREljSFCRERJY4gQEVHSGCJERJQ0hggRESWNIUJEREljiBARUdL+P0s+T90GGyBMAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "labels = ['Major Match', '']\n",
    "sizes = [273, 727]\n",
    "colors = ['#E2E2E2', '#6392BF']\n",
    "explode = (0, 0.08)\n",
    "plt.figure(figsize=(7, 7))\n",
    "plt.pie(sizes,\n",
    "        labels=labels,\n",
    "        explode=explode,\n",
    "        autopct='%1.1f%%',\n",
    "        colors=colors,\n",
    "        startangle=270,\n",
    "        shadow=True)\n",
    "# plt.savefig('major-match-job.png', transparent=True)\n",
    "plt.show()\n",
    "\n",
    "# data from:\n",
    "# https://libertystreeteconomics.newyorkfed.org/2013/05/do-big-cities-help-college-graduates-find-better-jobs.html"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "button": false,
    "deletable": true,
    "new_sheet": false,
    "run_control": {
     "read_only": false
    }
   },
   "source": [
    "绝大多数人终生都饱受**时间幻觉**的拖累。\n",
    "\n",
    "小时候觉得时间太长，那是幻觉；长大了觉得时间越来越快，那还是幻觉 —— 时间从来都是匀速的。最大的幻觉在于，总是以为 “时间不够了” —— 这个幻觉最坑人。许多年前，有一次我开导我老婆。她说，“啊？得学五年才行啊？！太长了！” 我说，\n",
    "\n",
    "> “你回头看看呗，想想呗，五年前你在做什么？是不是回头一看的时候，五年前就好像是昨天？道理是一样的，五年之后的某一天你回头想今天，也是 ‘一转眼五年就过去’ 了…… 只不过，你今天觉得需要时间太多，所以不肯学 —— 但是，不管你学还是不学，五年还是会 ‘一转眼就过去’ 的…… 到时候再回头，想起这事的时候，没学的你，一定会后悔 —— 事实上，你已经有很多次后悔过 ‘之前要是学了就好了’，不是吗？”\n",
    "\n",
    "现在回头看，开导是非常成功的。十多年后的今天，她已经真的可以被称为 “自学专家” —— 各种运动在她那儿都不是事。健身，可以拿个北京市亚军登上健与美杂志封面；羽毛球，可以参加专业比赛；潜水，潜遍全球所有潜水胜地，到最后拿到的各种教练证比她遇到的各地教练的都多、更高级；帆船，可以组队横跨大西洋；爬山，登上喜马拉雅……"
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    "都说，人要有一技之长。那这一技究竟应该是什么呢？\n",
    "\n",
    "> 自学能力是唯一值得被不断磨练的长技。\n",
    "\n",
    "磨练出自学能力的好处在于，无论这世界需要我们学什么的时候，我们都可以主动去学，并且还是马上开始 —— 不需要等别人教、等别人带。\n",
    "\n",
    "哪怕有很强的自学能力的意思也并不是说，什么都能马上学会、什么都能马上学好，到最后无所不精无所不通…… 因为这里有个时间问题。无论学什么，都需要耗费时间和精力，与此同时更难的事情在于不断填补耐心以防它过早耗尽。另外，在极端的情况下，多少也面临天分问题。比如身高可能影响打篮球的表现，比如长相可能影响表演的效果，比如唱歌跑调貌似是很难修复的，比如有些人的粗心大意其实是基因决定的，等等。不过，以我的观察，无论是什么，哪怕只是学会一点点，都比不会强。哪怕只是中等水平，就足够应付生活、工作、养家糊口的需求。\n",
    "\n",
    "我在大学里学的是会计专业，毕业后找不到对口工作，只好去做销售 —— 没人教啊！怎么办？自学。也有自学不怎么样的时候，比如当年研究生课程我就读不完。后来想去新东方教书 —— 因为听说那里赚钱多 —— 可英语不怎么样啊！怎么办？自学。离开新东方去创业，时代早就变了，怎么办？自学，学的不怎么样，怎么办？硬挺。虽然创业这事后来也没怎么大成，但竟然在投资领域开花结果 —— 可赚了钱就一切平安如意了吗？并不是，要面对之前从来没可能遇到的一些险恶与困境，怎么办？自学。除了困境之外，更痛苦的发现在于对投资这件事来说，并没有受过任何有意义的训练，怎么办？自学。觉得自己理解的差不多了，一出手就失败，怎么办？接着学。\n",
    "\n",
    "我出身一般，父母是穷教师。出生在边疆小镇，儿时受到的教育也一般，也是太淘气 —— 后来也没考上什么好大学。说实话，我自认天资也一般，我就是那种被基因决定了经常马虎大意的人。岁数都这么大了，情商也都不是一般的差 —— 还是跟年轻的时候一样，经常莫名其妙就把什么人给得罪透了……\n",
    "\n",
    "但我过得一直不算差。\n",
    "\n",
    "靠什么呢？人么，一个都靠不上。到最后，我觉得只有一样东西真正可靠 —— **自学能力**。于是，经年累月，我磨练出了一套属于我自己的本领：只要我觉得有必要，我什么都肯学，学什么都能学会到够用的程度…… 编程，我不是靠上课学会的；英语，不是哪个老师教我的；写作，也不是谁能教会我的；教书，没有上过师范课程；投资，更没人能教我 —— 我猜，也没人愿意教我…… 自己用的东西自己琢磨，挺好。\n",
    "\n",
    "关键在于，自学这事并不难，也不复杂，挺简单的，因为它所需要的一切都很朴素。\n",
    "\n",
    "于是，从某个层面上来看，我每天都过的很开心。为什么？因为我有未来。凭什么那么确信？因为我知道我自己有自学能力。\n",
    "\n",
    "**—— 我希望你也有。**\n",
    "\n",
    "准确地讲，希望你有个更好的未来。\n",
    "\n",
    "而现在我猜，此刻，你心中也是默默如此作想的罢。"
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